On the influence of US monetary policy on crude oil price volatility

Forecasting oil prices is not straightforward, such that it is convenient to build a confidence interval around the forecasted prices. To this end, the principal ingredient for obtaining a reliable crude oil confidence interval is its volatility. Moreover, accurate crude oil volatility estimation has fundamental implications in terms of risk management, asset pricing and portfolio handling. Generally, current studies consider volatility models based on lagged crude oil price realizations and, at most, one additional macroeconomic variable as crude oil determinant. This paper aims to fill this gap, jointly considering not only traditional crude oil driving forces, such as the aggregate demand and oil supply, but also the monetary policy rate. Thus, this work aims to contribute to the debate concerning the potential impact of (lagged) US monetary policy as well as the other crude oil future price (COFP) determinants on daily COFP volatility. By means of the recently proposed generalized autoregressive conditional heteroskedasticity mixed data sampling model, different proxies of the US monetary policy alongside US industrial production (proxy of the US aggregate demand) and oil supply are included in the COFP volatility equation. Strong evidence that an expansionary (restrictive) variation in monetary policy anticipates a positive (negative) variation in COFP volatility is found. We also find that a negative (positive) variation of industrial production increases (decreases) COFP volatility. This means that volatility behaves counter-cyclically, according to the literature. Furthermore, the out-of-sample forecasting procedure shows that including these additional macroeconomic variables generally improves the forecasting performance.     

Risk assessment of oil price from static and dynamic modelling approaches

The price gap between West Texas Intermediate (WTI) and Brent crude oil markets has been completely changed in the past several years. The price of WTI was always a little larger than that of Brent for a long time. However, the price of WTI has been surpassed by that of Brent since 2011. The new market circumstances and volatility of oil price require a comprehensive re-estimation of risk. Therefore, this study aims to explore an integrated approach to assess the price risk in the two crude oil markets through the value at risk (VaR) model. The VaR is estimated by the extreme value theory (EVT) and GARCH model on the basis of generalized error distribution (GED). The results show that EVT is a powerful approach to capture the risk in the oil markets. On the contrary, the traditional variance–covariance (VC) and Monte Carlo (MC) approaches tend to overestimate risk when the confidence level is 95%, but underestimate risk at the confidence level of 99%. The VaR of WTI returns is larger than that of Brent returns at identical confidence levels. Moreover, the GED-GARCH model can estimate the downside dynamic VaR accurately for WTI and Brent oil returns.     

The asymmetric effects of oil shocks on output growth: A Markov–Switching analysis for the G-7 countries

Oil shocks are generally acknowledged to have important effects on both economic activity and macroeconomic policy. The aim of this paper is to investigate how oil price shocks affect the growth rate of output of a subset of developed countries by comparing alternative regime switching models. Different Markov–Switching (MS) regime autoregressive models are, therefore, specified and estimated. In a successive step, univariate MS models are extended in order to verify if the inclusion of asymmetric oil shocks as an exogenous variable improves the ability of each specification to identify the different phases of the business cycle for each country under scrutiny. Following the wide literature on this topic, seven different definitions of oil shocks which are able to describe oil price changes, asymmetric transformations of oil price changes, oil price volatility, and oil supply conditions are considered.     

Realized volatility transmission: The role of jumps and leverage effects

This paper is the first to employ a multivariate extension of the LHAR–CJ model for realized volatility of Corsi and Renó (2012) considering continuous and jump volatility components and leverage effects. The model is applied to financial (S&P 500), commodity (WTI crude oil) and forex (US$/EUR) intraday futures data and allows new insights in the transmission mechanisms among these markets. Besides significant leverage effects, we find that the jump components of all considered assets do not contain incremental information for the one-step ahead realized volatility. The volatility of S&P 500 and US$/EUR exchange rate futures exhibits significant spillovers to the realized volatility of WTI. Moreover, decreasing equity prices appear to increase volatility in other markets, while strengthening of the US$ seems to calm down the crude oil market.     

Forecasting realized volatility of crude oil futures with equity market uncertainty

This paper examines whether the equity market uncertainty (EMU) index contains incremental information for forecasting the realized volatility of crude oil futures. We use 5-min high-frequency transaction data for WTI crude oil futures and develop six heterogeneous autoregressive (HAR) models based on classical HAR-type models. The empirical results suggest that EMU contains more incremental information than the economic policy uncertainty (EPU) for forecasting the realized volatility of crude oil futures. More importantly, we argue that EMU is a non negligible additional predictive variable that can significantly improve the 1-day ahead predictive accuracy of all six HAR-type models, and improve the 1-week ahead forecasting performance of the HAR-RV, HAR-RV-J, HAR-RSV, HAR-RV-SJ models. These findings highlight a strong short-term and a weak mid-term predictive ability of EMU in the crude oil futures market.     

Assessing dynamics of crude oil import demand in Korea

Although Korea was the world's seventh largest oil consumer and fourth largest oil importer, relatively little attention has been paid to empirical analyses of the Korean crude oil market. In this paper, we have attempted to expand the scope of previous literature by examining Korea's import demand for crude oil in a dynamic framework of cointegration. The empirical focus is on assessing the short- and long-run relationships among volume of crude oil import, economic growth and price of imported crude oil in Korea. For this purpose, an autoregressive distributed lag (ARDL) approach is applied to quarterly data for 1986–2010. Results show that income level is a more powerful determinant of the long-run behavior of Korea's crude oil imports than crude oil price. In the short-run, on the other hand, oil price is found to play a more important role in determining crude oil imports than income level.     

A study of Shanghai fuel oil futures price volatility based on high frequency data: Long-range dependence,modeling and forecasting

In existing researches, the investigations of oil price volatility are always performed based on daily data and squared daily return is always taken as the proxy of actual volatility. However, it is widely accepted that the popular realized volatility (RV) based on high frequency data is a more robust measure of actual volatility than squared return. Due to this motivation, we investigate dynamics of daily volatility of Shanghai fuel oil futures prices employing 5-minute high frequency data. First, using a nonparametric method, we find that RV displays strong long-range dependence and recent financial crisis can cause a lower degree of long-range dependence. Second, we model daily volatility using RV models and GARCH-class models. Our results indicate that RV models for intraday data overwhelmingly outperform GARCH-class models for daily data in forecasting fuel oil price volatility, regardless the proxy of actual volatility. Finally, we investigate the major source of such volatile prices and found that trader activity has major contribution to fierce variations of fuel oil prices.     

Conditional Markov regime switching model applied to economic modelling

In this paper we discuss the calibration issues of regime switching models built on mean-reverting and local volatility processes combined with two Markov regime switching processes. In fact, the volatility structure of these models depends on a first exogenous Markov chain whereas the drift structure depends on a conditional Markov chain with respect to the first one. The structure is also assumed to be Markovian and both structure and regime are unobserved. Regarding this construction, we extend the classical Expectation–Maximization (EM) algorithm to be applied to our regime switching model. We apply it to economic data (Euro/Dollar (USD) foreign exchange rate and Brent oil price) to show that such modelling clearly identifies both mean reverting and volatility regime switches. Moreover, it allows us to make economic interpretations of this regime classification as in some financial crises or some economic policies.     

A robust analysis of the relationship between renewable energy consumption and its main drivers

We provide a comprehensive and robust analysis of the drivers of renewable energy consumption for a panel of 64 countries, using both the static (Pooled OLS, Panel Fixed and Random Effects) and dynamic (difference and system GMM) panel data estimation approaches. We show that the dynamic panel data model provides more efficient estimators than the static ones and that increases in per capita CO₂ emissions and per capita trade with foreign partners mainly drive the changes in per capita renewable energy consumption. We also find limited evidence of oil price effects on renewable energy consumption, which reflects the fact that renewable energy is just a complement and not a perfect substitute of crude oil, at least in the short run.     

Asymmetric evidence of gasoline price responses in France: A Markov-switching approach

It has been documented that retail gasoline prices respond more quickly to increases in wholesale prices than they do to decreases in wholesale prices. However, there is little empirical evidence that identifies the link between the pass-through of oil prices to gasoline in different volatility regimes. Using a Markov-switching model on weekly observations of fuel prices from 1990 to 2011, we find that fuel prices respond significantly faster to increases in crude oil prices than to decreases in crude oil prices. However, when volatility is low, the transmittal of a price change from crude oil to retail fuel is higher compared to periods of high volatility. These results provide important information on the behavior of retailers. The findings of this paper therefore provide clues for better understanding the recent dynamics of fuel prices and some policy implications.     

Forecasting the oil futures price volatility: A new approach

This study provides a new perspective of modelling and forecasting realized range-based volatility (RRV) for crude oil futures. We are the first to improve the Heterogeneous Autoregressive model of Realized Range-based Volatility (HAR-RRV) model by considering the significant jump components, signed returns and volatility of realized range-based volatility. The empirical results show that the volatility of volatility significantly exists in the oil futures market. Moreover, our new proposed models with significant jump components, signed returns and volatility of volatility can gain higher forecast accuracy than HAR-RRV-type models. The results are robust to different forecasting windows and forecasting horizons. Our new findings are strategically important for investors making better decisions.     

An asymmetric analysis of the relationship between oil prices and output: The case of Turkey

In this paper we analyze the asymmetric impact of oil price changes on the economic activity in Turkey. In contrast to previous studies on Turkey, the existence of an asymmetric relationship between economic activity and oil prices is investigated by regime-dependent impulse response functions and forecast error variance decompositions based on a multivariate two-regime Threshold VAR (TVAR) model. Our analysis suggests that the relationship between oil prices and macroeconomic activity is nonlinear and exhibits an asymmetric pattern: oil price changes have a significant effect on inflation and output when the change exceeds a certain threshold level. The lower response of macroeconomic variables to oil price shocks in the low oil price change regime also indicates that only the shocks exceeding the optimal threshold level are able to create a contraction in the economic activity.     

国际原油价格波动对我国工业品出厂价格的影响——基于行业层面的实证分析

随着我国石油消费量和进口量的不断增长,国际原油价格的波动对我国经济的影响越来越大。基于38个行业的月度数据,本文详细分析了2003年1月-2009年2月国际原油价格波动对我国PPI指数的影响,研究发现:尽管为了降低国际油价对国内经济的冲击,政府仍对成品油定价体制实行部分调控,但国际原油价格的波动对我国PPI指数仍具有重要影响,尤其是生产资料价格以及石化行业等高耗能行业,而这主要与各行业的能源消费总量和能源利用效率有关。为此,我国应加快国内成品油定价体制改革,实施有效的产业政策,以促使各行业提高其能源利用效率,并最终有效地降低国际油价波动给我国经济带来的价格效应。     

GLOBAL OIL PRICES,OIL INDUSTRY AND EQUITY RETURNS: RUSSIAN EXPERIENCE

The purpose of this paper is to promote a greater understanding of the implications of oil price changes on the equity investment climate in Russia. A dynamic bivariate exponential general autoregressive conditional heteroscedastic (EGARCH) analysis shows that global oil price returns have significant impact on Russian equity returns and volatility. At the same time, a dynamic correlation analysis highlights Russia's importance in the international geopolitical scene and its positioning as a reliable supplier of oil during times of turmoil in the Middle East. There are a number of challenges, however, that threaten to slow down the performance of the oil industry in Russia and compromise the country's future economic growth and stock market performance.     

Responses of international stock markets to oil price surges: a regime-switching perspective

We propose an enhanced regime-switching model to investigate the relationships between oil price surges and stock market cycles in five oil-dependent countries. Our model accounts for the joint effects of the West Texas Intermediate (WTI) and Brent oil markets and simultaneously captures asymmetry, volatility persistence and regime shifts contained in the underlying financial data. We find that stock market returns strongly exhibit a regime-switching behaviour, but they react differently to the increases in the price of oil. More precisely, the conditional volatility of studied stock markets during the bear market phases is found to be less affected by oil price surges than during the bull market phases. Whether the effects of oil shocks are positive or negative depends greatly on the degree of reliance on imported oil, the share of the cost of oil in the national income and the degree of improvement in energy efficiency of a given country. Finally, the relatively opposite effects of the WTI and Brent oil markets suggest the potential of substitution between them as well as the necessity of a diversification strategy of oil supply sources.     

房价与经济波动的区制转移——基于STAR系列模型的实证研究

本文运用平滑转移自回归(STAR)系列模型定量分析了1998-2010年间我国经济波动区制转移(Regime Transition)过程及房价波动在其中的作用。研究结果表明,我国经济在受到外生刺激时会产生跳跃冲动,但能否出现区制转移现象取决于外生刺激的持续性,单纯依靠以往经济的表现不能充分地解释这种现象;房价作为外生变量有效地解释了经济波动中存在的动态转移过程,这表明房价波动中存在着先行信息并可用于预测未来经济走向。此外,经济波动转移过程并非不可逆转,足够的反向推动力能够扭转经济势头,这使得政策干预成为可能。     

A dynamic Nelson-Siegel yield curve model with Markov switching

This paper proposes a model to better capture persistent regime changes in the interest rates of the US term structure. While the previous literature on this matter proposes that regime changes in the term structure are due to persistent changes in the conditional mean and volatility of interest rates we find that changes in a single parameter that determines the factor loadings of the model better captures regime changes. We show that this model gives superior in-sample forecasting performance as compared to a baseline model and a volatility-switching model. In general, we find compelling evidence that the extracted factors from our term structure models are closely related with various economic variables. Furthermore, we investigate and find evidence that the effects of macroeconomic phenomena such as monetary policy, inflation expectations, and real economic activity differ according to the particular regime realized for the term structure. In particular, we identify the periods where monetary policy appears to have a greater effect on the yield curve, and the periods where inflation expectations seem to have a greater effect in yield determination. We also find convincing evidence of a relationship between the regimes estimated by the various switching models with economic activity and monetary policy.     

Inflation,oil price volatility and monetary policy

In a fully micro-founded New Keynesian framework, we characterize an analytical relationship between average inflation and oil price volatility by solving the rational expectations equilibrium of the model up to second order of accuracy. The model shows that higher oil price volatility induces higher levels of average inflation. We also show that when oil has low substitutability in the production function, the higher the weight the central bank assigns to inflation in the policy rule, the lower the level of average inflation is. The analytical solution further indicates that, for a given level of oil price volatility, average inflation is higher when marginal costs are convex in oil prices, the Phillips Curve is convex, and the degree of relative price dispersion is higher. The evolution of inflation during the 70s and 80s is consistent with the prediction of the model.     

What to stabilize in the open economy*

We consider the question how “best” to maintain price‐level stability in an open economy, and evaluate three possible policy choices: (a) a constant money growth rate rule; (b) a fixed exchange rate; and (c) a policy of explicit commitment to a price‐level target. In each case we assume that policy is conducted by injecting reserves into or withdrawing reserves from the “banking system.” In evaluating the three regimes, we adopt the criterion that the “best” policy should leave the least scope for indeterminacy and “excessive” economic volatility. In a steady‐state equilibrium, the choice of regime is largely irrelevant; any steady‐state equilibrium under one regime can be duplicated by an appropriate choice of the “control” variable under any other regime. However, we show that the sets of equilibria under the three regimes are dramatically different. When all countries follow the policy of fixing a constant rate of money growth, there are no equilibria displaying endogenously arising volatility and there is no indeterminacy of equilibrium. Under a regime of fixed exchange rates, indeterminacies and endogenously arising fluctuations are impossible if and only if the country with the low “reserve‐to‐deposit” ratio is charged with maintaining the fixed rate. Finally, when one country targets the time path of its price level, under very weak conditions, there will be indeterminacy of equilibrium and endogenously arising volatility driven by expectations.     

考虑价格因素的原油进口多元化路径研究

价格风险是我国原油进口面临的主要风险之一,通过构建我国原油进口的价格-风险模型,量化研究了我国原油进口来源国的最优风险结构。结论显示,中东地区依然是我国最重要的原油进口来源地,进口更多来自政治稳定地区的原油,可以有效地分散我国原油的供应风险。从长期来看,我国需要积极拓展更多的石油供应渠道,进一步提高从阿联酋、美国、澳大利亚、加拿大、哈萨克斯坦、埃及以及卡塔尔的进口量,保证我国的原油进口安全。